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At least 127 records · Page 7Linked to original sources
USGS2021

An adaptive management implementation framework for evaluating supplemental sea lamprey (Petromyzon marinus) controls in the Laurentian Great Lakes

Invasive sea lamprey ( Petromyzon marinus ) populations in the Laurentian Great Lakes Basin have been suppressed for over 60 years primarily by migration barriers and lamprey-specific pesticides. Improving control outcomes by supplementing barriers and pesticides with additional control strategies has been a long-standing objective of managers and stakeholders, but progress towards this objective has been limited. We developed an adaptive management implementation framework and applied it to this objective. The framework consists of a set of adaptive management implementation goals (develop effective monitoring practices, develop effective participatory process, and conduct management experiments), a set of aspirational targets hypothesized to be related to Sea Lamprey Control Program adaptive capacity (multi-level political and social organization, creation of safe-to-fail decision making arenas, and effective use of multi-criteria decision analysis), and a feedback loop linking adaptive capacity and progress towards adaptive management implementation goals. Progress towards improving sea lamprey control outcomes by integrating supplemental control strategy into the Sea Lamprey Control Program may be possible through adaptive management implementation.

Great Lakes↗
USGS2018

Managing the vanishing North American hunter: A novel framework to address declines in hunters and hunter-generated conservation funds

As long as the funding mechanism supporting state wildlife conservation relies heavily on hunter-generated funds, declines in hunter participation are a threat to the conservation of both game and non-game species. To address options to bolster wildlife agency profit from the sale of hunting licenses, we developed a stage-based, stochastic population model of a hunter population, and demonstrate its utility within a decision-making framework to inform state wildlife agency decisions. We evaluated hypothetical youth and adult recruitment-focused outreach programs over 10 years to increase license sale profit. Using our model as the core of a decision analysis, state agencies can set hunter population or license profit targets, and evaluate management actions designed to achieve those objectives. We anticipate that our approach will provide a valuable framework for anticipating the future of hunting and hunting-generated conservation funds, and can be extended to other user groups, including target shooters and anglers.

Human Dimensions of Wildlife: An International Jou↗
USGS2011

An adaptive-management framework for optimal control of hiking near golden eagle nests in Denali National Park

Unintended effects of recreational activities in protected areas are of growing concern. We used an adaptive-management framework to develop guidelines for optimally managing hiking activities to maintain desired levels of territory occupancy and reproductive success of Golden Eagles (Aquila chrysaetos) in Denali National Park (Alaska, U.S.A.). The management decision was to restrict human access (hikers) to particular nesting territories to reduce disturbance. The management objective was to minimize restrictions on hikers while maintaining reproductive performance of eagles above some specified level. We based our decision analysis on predictive models of site occupancy of eagles developed using a combination of expert opinion and data collected from 93 eagle territories over 20 years. The best predictive model showed that restricting human access to eagle territories had little effect on occupancy dynamics. However, when considering important sources of uncertainty in the models, including environmental stochasticity, imperfect detection of hares on which eagles prey, and model uncertainty, restricting access of territories to hikers improved eagle reproduction substantially. An adaptive management framework such as ours may help reduce uncertainty of the effects of hiking activities on Golden Eagles

Alaska↗
USGS2018

Prioritizing conserved areas threatened by wildfire and fragmentation for monitoring and management

In many parts of the world, the combined effects of habitat fragmentation and altered disturbance regimes pose a significant threat to biodiversity. This is particularly true in Mediterranean-type ecosystems (MTEs), which tend to be fire-prone, species rich, and heavily impacted by human land use. Given the spatial complexity of overlapping threats and species’ vulnerability along with limited conservation budgets, methods are needed for prioritizing areas for monitoring and management in these regions. We developed a multi-criteria Pareto ranking methodology for prioritizing spatial units for conservation and applied it to fire threat, habitat fragmentation threat, species richness, and genetic biodiversity criteria in San Diego County, California, USA. We summarized the criteria and Pareto ranking results (from west to east) within the maritime, coastal, transitional, inland climate zones within San Diego County. Fire threat increased from the maritime zone eastward to the transitional zone, then decreased in the mountainous inland climate zone. Number of fires and fire return interval departure were strongly negatively correlated. Fragmentation threats, particularly road density and development density, were highest in the maritime climate zone, declined towards the east, and were positively correlated. Species richness criteria showed distributions among climate zones similar to those of the fire threat variables. When using species richness and fire threat criteria, most lower-ranked (higher conservation priority) units occurred in the coastal and transitional zones. When considering genetic biodiversity, lower-ranked units occurred more often in the mountainous inland zone. With Pareto ranking, there is no need to select criteria weights as part of the decision-making process. However, negative correlations and larger numbers of criteria can result in more units assigned to the same rank. Pareto ranking is broadly applicable and can be used as a standalone decision analysis method or in conjunction with other methods.

California↗
USGS2014

Brine contamination to aquatic resources from oil and gas development in the Williston Basin, United States

The Williston Basin, which includes parts of Montana, North Dakota, and South Dakota in the United States and the provinces of Manitoba and Saskatchewan in Canada, has been a leading domestic oil and gas producing region for more than one-half a century. Currently, there are renewed efforts to develop oil and gas resources from deep geologic formations, spurred by advances in recovery technologies and economic incentives associated with the price of oil. Domestic oil and gas production has many economic benefits and provides a means for the United States to fulfill a part of domestic energy demands; however, environmental hazards can be associated with this type of energy production in the Williston Basin, particularly to aquatic resources (surface water and shallow groundwater) by extremely saline water, or brine, which is produced with oil and gas. The primary source of concern is the migration of brine from buried reserve pits that were used to store produced water during recovery operations; however, there also are considerable risks of brine release from pipeline failures, poor infrastructure construction, and flow-back water from hydraulic fracturing associated with modern oilfield operations. During 2008, a multidisciplinary (biology, geology, water) team of U.S. Geological Survey researchers was assembled to investigate potential energy production effects in the Williston Basin. Researchers from the U.S. Geological Survey participated in field tours and met with representatives from county, State, tribal, and Federal agencies to identify information needs and focus research objectives. Common questions from agency personnel, especially those from the U.S. Fish and Wildlife Service, were “are the brine plumes (plumes of brine-contaminated groundwater) from abandoned oil wells affecting wetlands on Waterfowl Production Areas and National Wildlife Refuges?” and “are newer wells related to Bakken and Three Forks development different than the older, abandoned wells (in terms of potential for affecting aquatic resources)?” Of special concern were the wetland habitats of the ecologically important Prairie Pothole Region, which overlays a part of the Williston Basin and is recognized for the production of a majority of North America’s migratory waterfowl. On the basis of the concerns raised by on-the-ground land managers, as well as findings from previous research, a comprehensive study was developed with the following goals: summarize existing information pertaining to oil and gas production and aquatic resources in the Williston Basin; assess brine plume migration from new and previously studied sites in the Prairie Pothole Region; perform a regional, spatial evaluation of oil and gas production activities and aquatic resources; assess the potential for brine contamination to wetlands and streams; and hold a decision analysis workshop with key stakeholders to discuss issues pertaining to oil and gas production and environmental effects and to identify information gaps and research needs. This report represents an initial, multidisciplinary evaluation of measured and potential environmental effects associated with oil and gas production in the Williston Basin and Prairie Pothole Region. Throughout this report there are reviews of current knowledge, and discussions relating to data gaps and research needs. On the basis of the information presented, future research needs include: regional geophysical and water-quality assessments to establish baselines for current conditions and estimate the extent of previous brine contamination, investigations into the direct effects of brine to biotic communities, and evaluations to identify the most effective techniques to mitigate brine contamination.

Montana, North Dakota↗
USGS2013

Resilience thinking and a decision-analytic approach to conservation: strange bedfellows or essential partners?

There has been some tendency to view decision science and resilience theory as opposing approaches, or at least as contending perspectives, for natural resource management. Resilience proponents have been especially critical of optimization in decision science, at least for those cases where it is focused on the aggressive pursuit of efficiency. In general, optimization of resource systems is held to reduce spatial, temporal, or organizational heterogeneity that would otherwise limit efficiency, leading to homogenization of a system and making it less able to cope with unexpected changes or disturbances. For their part, decision analysts have been critical of resilience proponents for not providing much practical advice to decision makers. We believe a key source of tension between resilience thinking and application of decision science is the pursuit of efficiency in the latter (i.e., choosing the “best” management action or strategy option to maximize productivity of one or few resource components), vs. a desire in the former to keep options open (i.e., maintaining and enhancing diversity). It seems obvious, however, that with managed natural systems, there must be a principle by which to guide decision making, which at a minimumallows for a comparison of projected outcomes associated with decision alternatives. This is true even if the primary concern of decision making is the preservation of system resilience. We describe how a careful framing of conservation problems, especially in terms of management objectives and predictive models, can help reduce the purported tension between resiliencethinking and decision analysis. In particular, objective setting in conservation problems needs to be more attuned to the dynamics of ecological systems and to the possibility of deep uncertainties that underlie the risk of unintended, if not irreversible, outcomes. Resilience thinking also leads to the suggestion that model development should focus more on process rather than pattern, on multiple scales of influence, and on phenomena that can create alternative stability regimes. Although we acknowledge the inherent difficulties in modeling ecological processes, we stress that formulation of useful models need not depend on a thorough mechanistic understanding or precise parameterization, assuming that uncertainty is acknowledged and treated in a systematic manner.

Ecology and Society↗
USGS2004

Evolution of quantitative methods for the study and management of avian populations: on the importance of individual contributions

The EURING meetings and the scientists who have attended them have contributed substantially to the growth of knowledge in the field of estimating parameters of animal populations. The contributions of David R. Anderson to process modeling, parameter estimation and decision analysis are briefly reviewed. Metrics are considered for assessing individual contributions to a field of inquiry, and it is concluded that Anderson’s contributions have been substantial. Important characteristics of Anderson and his career are the ability to identify and focus on important topics, the premium placed on dissemination of new methods to prospective users, the ability to assemble teams of complementary researchers, and the innovation and vision that characterized so much of his work. The paper concludes with a list of interesting current research topics for consideration by EURING participants.

Animal Biodiversity and Conservation↗
USGS1980

Research on interactive genetic-geological models to evaluate favourability for undiscovered uranium resources

Current methods of evaluating favourability for undiscovered uranium resources are unduly subjective, quite possibly inconsistent and, as a consequence, of questionable reliability. This research is aimed at reducing the subjectivity and increasing the reliability by designing an improved method that depends largely on geological data and their statistical frequency of occurrence. This progress report outlines a genetic approach to modelling the geological factors that controlled uranium mineralization in order to evaluate the favourability for the occurrence of undiscovered uranium deposits of the type modeled. A genetic model is constructed from all the factors that describe the processes, in chronological sequence, that formed uranium deposits thought to have a common origin. The field and laboratory evidence for the processes constitute a geologic occurrence base that parallels the chronological sequence of events. The genetic model and the geologic-occurrence base are portrayed as two columns of an interactive matrix called the "genetic-geologic model". For each column, eight chronological stages are used to describe the overall formation of the uranium deposits. These stages consist of (1) precursor processes; (2) host-rock formation; (3) preparation of host-rock; (4) uranium-source development; (5) transport of uranium; (6) primary uranium deposition; (7) post-deposition modification; and (8) preservation. To apply the genetic-geological model to evaluate favourability, a question is posed that determines the presence or absence of each attribute listed under the geologic-occurrence base. By building a logic circuit of the attributes according to either their essential or non-essential nature, the resultant match between a well-documented control area and the test area may be determined. The degree of match is a measure of favourability for uranium occurrence as hypothesized in the genetic model. This process of geological decision analysis results in a series of favourability maps that can be combined into a final composite favourability map.

Conference Paper↗
USGS2020

Keeping Hawai‘i's forest birds one step ahead of disease in a warming world

Hawai‘i’s high-elevation forests provide a critical refuge from disease for native forest birds. However, global warming is facilitating the encroachment of mosquitoes and the diseases they transmit into increasingly higher elevations of remaining refugia, threatening the viability of the forest birds across the islands. Multiple management actions to address the threat of disease have been proposed, but there is an urgent need to identify which actions (or series of actions) should be prioritized as most effective, most cost-efficient, and most likely to produce results at a pace sufficient to stay ahead of climate change. A group of scientists, managers, and policy makers convened to evaluate a set of possible conservation strategies under a structured decision-making framework, focusing on management of Hakalau Forest National Wildlife Refuge, which was established to protect native Hawai‘ian forest birds. The biological models necessary to evaluate the set of conservation actions identified are not yet available, but the process of developing the framework for the decision analysis was immensely valuable for framing the issues and identifying information needs. Lessons learned from Hakalau Forest will be applicable to many other areas in Hawai‘i facing the same threat to forest birds.

Hawaii↗
USGS2017

Value of information analysis as a decision support tool for biosecurity

This chapter demonstrates the economic concept of ‘value of information’(VOI), and how biosecurity managers can use VOI analysis to decide whether or not to reduce uncertainty by collecting additional information through monitoring, experimentation, or some other form of research. We first explore how some uncertainties may be scientifically interesting to resolve, but ultimately irrelevant to decision-making. We then develop a prototype model where a manager must choose between eradication or containment of an infestation. Eradication is more cost-effective for smaller infestations, but once the extent reaches a certain size it becomes more cost-effective to contain. When choosing between eradication and containment, how much does knowing the extent of the infestation more exactly improve the outcome of the decision? We calculate the expected value of perfect information (EVPI) about the extent, which provides an upper limit for the value of reducing uncertainty. We then illustrate the approach using the example of red imported fire ant management in south-east Queensland. We calculate the EVPI for three different uncertain variables: the extent of the infestation, the sensitivity (true positive rate) of remote sensing, and the efficacy of baiting.

Book chapter↗
USGS2026

Colocating artificial intelligence data centers with energy infrastructure on Federal public lands—A science synthesis and spatial analysis to inform decision making

Executive Summary Artificial intelligence (AI) is rapidly transforming industries and economies, creating an urgent need to strategically plan for the energy and infrastructure required to support increasing AI use. U.S. Federal agencies and bureaus have been directed to explore ways to accelerate permitting, development, and deployment of energy resources and AI technologies, including encouraging the colocation of energy infrastructure and data centers. To inform these initiatives, this report synthesizes relevant scientific information and presents a spatial analysis of existing energy infrastructure and data centers on or near U.S. Federal public lands managed by the Bureau of Land Management (BLM). The purpose of this science synthesis and spatial analysis is to provide the BLM with foundational information for considering potential colocation of data centers with energy infrastructure on Federal public lands to support evidence-based decisions. Additionally, this report provides insight into current (2025) and potential future energy demands by providing projections of a range of potential future environmental conditions relevant to maintaining industry-recommended cooling temperature standards necessary for efficient data center operations. As a part of this effort, a rapid response literature review was conducted of the best available science on the topic of data center development and energy infrastructure in July–August 2025, supplemented by additional resources recommended by U.S. Federal agency and bureau subject matter experts (hereafter experts; including the U.S. Department of Energy National Laboratory of the Rockies) and peer reviewers. To better understand current conditions relevant to AI data center development, a spatial analysis was conducted across Alaska and 11 States in the Western United States, Arizona, California, Colorado, Idaho, Montana, Nevada, New Mexico, Oregon, Utah, Washington, and Wyoming, all of which contain extensive BLM-managed surface lands (hereafter referred to as “BLM lands”) that could be considered for the colocation of energy infrastructure and AI data centers. This effort identified BLM lands within 10 miles of existing transmission lines, consistent with methods used in previous BLM programmatic environmental impact statements. This report describes the types of data centers operating within the United States, which vary in ownership, size, technology, and proximity to end users. This report then outlines the primary considerations of data center development, including reliable energy supply, natural resources (such as water availability to support cooling requirements), and relevant policy and regulatory considerations. Energy supply considerations are pivotal for data center operation. Between 2014 and 2018, data centers in the United States accounted for nearly 2 percent of the Nation’s total electricity consumption, and data center energy consumption is projected to increase from 2 to 6.7–12 percent of total U.S. electricity use by 2028. These energy requirements necessitate careful consideration of energy supply when considering potentially suitable locations for data center development. Experts anticipate that an increase in renewable energy generation will likely support most potential future power demand needs, including for data centers, followed by increases in natural gas, nuclear, and geothermal energy production. Additional capacity in the form of battery storage will likely not generate electricity, but may improve the reliability and flexibility of supply, helping to ensure that growing data center loads can be met. However, the U.S. Department of Energy estimates that the United States will need, on average, 57 percent more energy transmission infrastructure by 2035 to account for the growing power demand introduced by development such as data centers. Cooling server equipment in data centers requires large amounts of electricity and water, and this demand can be exacerbated by hot and humid conditions. Energy efficient water-based cooling technologies may reduce electricity consumption onsite but require more water consumption. This additional water demand has the potential to increase water stress and competition with other users. As such, developing data centers will likely need a thorough assessment of current and potential future water availability, as well as consideration of how water demand may change across other sectors. Data center development involves policy and regulatory considerations, as projects must undergo environmental review and authorization processes that can take 18–24 months. Coordinating these environmental reviews and authorizations with other energy development projects, such as building new transmission lines, may cause additional delays. Recent efforts by the U.S. Department of Energy and U.S. Department of the Interior aim to expedite environmental reviews and authorizations and improve coordination across agencies. The spatial analysis identified 771 existing AI data centers and more than 3,300 power plants. The spatial analysis found that 6 percent of AI data centers and 22 percent of power plants in the Western United States were on or within 1 mile of BLM lands, and California had the largest number of facilities. Most existing AI data centers were near high-voltage transmission lines and close to power plants, supporting efficient energy delivery. More than 90,000,000 acres of BLM lands were within 10 miles of existing high-voltage transmission lines, representing 38 percent of BLM lands in the study area. Available transmission infrastructure and the overlap with BLM lands varied by State, and Alaska had limited overlap compared to the rest of the Western United States. To operate most efficiently, data center temperatures must be at or below 80.6 degrees Fahrenheit. This analysis of future temperature and precipitation projections indicated increasing cooling demands for data centers, particularly in Arizona, California, and Nevada, where rising temperatures are expected to increase energy and operational costs while potentially stressing current regional electrical grid infrastructure. This report highlights relevant energy supply, natural resources, and regulatory considerations for data center development on BLM lands. This report does not provide a comprehensive ecological, regulatory, land suitability, or permitting analysis. The factors described here are contextual considerations only and are not intended to identify, rank, quantify, or recommend optimal areas for data center colocation. This spatial analysis focused solely on energy considerations relevant to data centers and did not consider water availability, critical habitats, BLM National Conservation Lands, areas of cultural or historical significance, and other sensitive resources. These topics are recognized as critical but were not within the scope of this science synthesis and spatial analysis.

Scientific Investigations Report↗
USGS2014

Collaborative modelling and integrated decision support system analysis of a developed terminal lake basin

A terminal lake basin in west-central Nevada, Walker Lake, has undergone drastic change over the past 90 yrs due to upstream water use for agriculture. Decreased inflows to the lake have resulted in 100 km 2 decrease in lake surface area and a total loss of fisheries due to salinization. The ecologic health of Walker Lake is of great concern as the lake is a stopover point on the Pacific route for migratory birds from within and outside the United States. Stakeholders, water institutions, and scientists have engaged in collaborative modeling and the development of a decision support system that is being used to develop and analyze management change options to restore the lake. Here we use an integrated management and hydrologic model that relies on state-of-the-art simulation capabilities to evaluate the benefits of using integrated hydrologic models as components of a decision support system. Nonlinear feedbacks among climate, surface-water and groundwater exchanges, and water use present challenges for simulating realistic outcomes associated with management change. Integrated management and hydrologic modeling provides a means of simulating benefits associated with management change in the Walker River basin where drastic changes in the hydrologic landscape have taken place over the last century. Through the collaborative modeling process, stakeholder support is increasing and possibly leading to management change options that result in reductions in Walker Lake salt concentrations, as simulated by the decision support system.

Nevada↗
USGS2024

A literature review and hypsometric analysis to support decisions on trout management flows on the Colorado River downstream from Glen Canyon Dam

Executive Summary Fish stranding has been studied in select rivers worldwide, often with the purpose of determining how to mitigate adverse effects of dam operations on highly valued salmon and trout populations. However, where a reduction in trout population size is desired by resource managers, as is the case downstream of the Glen Canyon Dam on the Colorado River, flow manipulations termed trout management flows (TMFs) may be used to optimize fish stranding and mortality. To inform the design and implementation of potential future TMFs, we reviewed relevant literature to identify key factors that influence fish stranding. We found that key factors were highly interdependent and site-specific, but general trends suggest that down-ramping (decreasing flow) at rapid rates in daytime during the late spring to summer emergence period would lead to stranding of age-0 rainbow trout in shallow shoreline habitat. A hypsometric analysis was then used to predict stranding risk for age-0 rainbow trout in Glen Canyon for a range of TMFs, which incorporated existing bathymetric data and flow and habitat suitability models. Our results indicate that a TMF with a steady high flow ranging from 12,000 to 16,000 cubic feet per second (ft 3 /s) combined with a minimum flow ranging from 3,000 to 5,000 ft 3 /s may effectively strand age-0 fish while also minimizing risk to water storage in Lake Powell and other resources. This strategy implemented under normal hydropeaking operations was predicted to lead to a substantive stranding risk when paired with low flows of 5,000 ft 3 /s, and especially 3,000 ft 3 /s. However, there remains uncertainty associated with elements of implementing an effective TMF downstream from Glen Canyon Dam. The main uncertainties include (1) the down-ramp rate that maximizes stranding of age-0 trout, (2) the duration of drawdown to maximize stranding mortality while minimizing impact to downstream resources, (3) duration of high flows required for age-0 fish to colonize newly created shoreline habitat (this is only for certain TMF hydrographs), (4) number of repetitions of TMF cycles to minimize compensatory survival response, and (5) recruitment threshold of both rainbow and brown trout populations to trigger TMF implementation.

Arizona↗
USGS2016

Application of effective discharge analysis to environmental flow decision-making

Well-informed river management decisions rely on an explicit statement of objectives, repeatable analyses, and a transparent system for assessing trade-offs. These components may then be applied to compare alternative operational regimes for water resource infrastructure (e.g., diversions, locks, and dams). Intra- and inter-annual hydrologic variability further complicates these already complex environmental flow decisions. Effective discharge analysis (developed in studies of geomorphology) is a powerful tool for integrating temporal variability of flow magnitude and associated ecological consequences. Here, we adapt the effectiveness framework to include multiple elements of the natural flow regime (i.e., timing, duration, and rate-of-change) as well as two flow variables. We demonstrate this analytical approach using a case study of environmental flow management based on long-term (60 years) daily discharge records in the Middle Oconee River near Athens, GA, USA. Specifically, we apply an existing model for estimating young-of-year fish recruitment based on flow-dependent metrics to an effective discharge analysis that incorporates hydrologic variability and multiple focal taxa. We then compare three alternative methods of environmental flow provision. Percentage-based withdrawal schemes outcompete other environmental flow methods across all levels of water withdrawal and ecological outcomes.

Environmental Management↗
USGS2020

Introduction to risk analysis

Many decisions are made in the face of uncertainty that either cannot or will not be reduced, and the challenge to the decision maker is how to manage the risk imposed by that uncertainty. This chapter will introduce the field of risk analysis, focusing on both the scientific tasks (estimating the probabilities and magnitudes of possible outcomes) and the policy-relevant value judgments needed (understanding the risk tolerances of the decision makers and stakeholders). The three case studies that follow demonstrate a range of approaches to risk management in a natural resource setting.

Book chapter↗
USGS1997

Use of a spatial decision support system for analysis of habitat use by wintering northern pintails

A multi-functional spatial decision support system (SDSS) was,developed at the spatial analysis branch Of the National Wetlands Research Center, and the wildlife analysis module of the system was used to study habitat use by wintering pintail. We instrumented female pintails at Catahoula Lake, Louisiana, in October of 1992-94 and located the instrumented birds weekly through the following March. Using the SDSS developed in an ARC/INFO geographical information system (GIS) - environment. We were able to visualize movements of instrumented pintails over varied environmental conditions and landscape features to determine habitat use. Weather data were used to determine factors important in the timing of movements. The analyses indicated that female pintails dispersed from Catahoula Lake, Louisiana, in three general patterns, based upon wetland conditions. Timing of movements coincided with periods of precipitation or disturbance, primarily hunting. Pintails which arrived at Catahoula Lake in October and November remained in the agricultural areas of Louisiana and Arkansas, with very limited movements to the coastal marshes or westward into the agricultural areas of Texas. Northward movements into Arkansas occurred whenever there was substantial rainfall in the agricultural regions, and northward movements generally stopped at the frost-line. No differences in adult or juvenile female movement patterns were apparent.

Louisiana↗